Comparative phytochemical profiling of three medicinal Polygonaceae plants using integrated molecular networking and...

The chemical complexity of medicinal plants poses a significant challenge for metabolomic profiling and chemotaxonomic discrimination. In this study, we applied an integrated pipeline combining Global Natural Products Social Molecular Networking (GNPS) platform with SIRIUS-based in silico annotation to systematically profile and compare the metabolomes of three medicinal Polygonaceae plants: Rheum palmatum, Polygonum cuspidatum, and Polygonum multiflorum. Beyond routine library matching, we implemented a data-mining strategy combining spectral networking and in silico structure annotation to extract characteristic MS/MS fragmentation features with chemotaxonomic relevance. Our results reveal distinct metabolic fingerprints among the three species and demonstrate that this integrated approach provides an efficient platform for comparative phytochemical studies, supporting chemotaxonomic classification and quality control of medicinal plants.